The present invention relates generally to the field of databases, and more particularly to tabular data applications and tabular data.
Ad-hoc analytic tools can operate in spreadsheets in order to, for example, return received query results. Reports with tabular data use ad-hoc analysis as all the data may not be relevant to each query and the data modeling may have been required. Manual data modeling may be more time consuming and expensive than automatic modeling tools. Modeling tools may contain predetermined assumptions about the data being modelled. Predetermined assumptions may be necessary for current applications to function but can lead to incorrect or incomplete query results.
A common assumption in modeling tools is the format of the layout of the received tabular data. Two common layouts are columnar or pivot table. In a columnar format, the first row of data provides the names of each column, and each subsequent row provides the values for a given record of data in each column. In a pivot table format the first row(s) and column(s) describe unique members (unique contexts), and each of the other cells provide the value at the intersections of these contexts.
It is possible that an application may receive tabular data containing a mix of columnar and pivot table format data. Importing mixed format tabular data into an ad-hoc tool may result in the entire dataset being interpreted as a single format, for example columnar. This assumption may lead to the tool creating unique hierarchies for each of a set of members, or columns, despite one or more columns containing conceptually similar data in the same hierarchy. This creates a very large model with limited usability.